Application demands are now outpacing Moore's law. Data acquisition, execution, and control requirements are reaching nanosecond time scales in the fields of communications, aerospace, and finance. For example, hypersonic aerial vehicles require sophisticated control algorithms that operate with high precision on smaller time scales. The implementation of sub-microsecond high frequency trading algorithms and large-scale Monte Carlo simulations require highly specialized hardware to match performance objectives in algorithmic finance. Other application areas include live packet inspection, routing, server control optimization, and image processing. All of these systems rely on low-latency solutions to computational problems that contain numerous variables. Currently, these problems are addressed by high performance electronic digital signal processing (DSP) hardware and field programmable gate arrays (FPGAs). However, state-of-the-art processors are reaching fundamental barriers in their interconnectivity, power efficiency, and speed.
Integrated photonic platforms represent an alternative to microelectronic approaches. The communication potentials of optical interconnects (bandwidth, energy use, electrical isolation) are expected to alleviate many of the communication bottlenecks in conventional computers that have contributed to the end of Moore's law in power consumption. Techniques in silicon photonic integrated circuit (PIC) fabrication are driven by a tremendous demand for optical interconnects within conventional digital computing systems. The first platforms for systems integration of active photonics are becoming a commercial reality and promise to bring economies of integrated circuit manufacturing to optical systems.
Optical devices and interconnects have received attention in the past, particularly in regards to neural networking. However, attempts to realize holographic or matrix-vector multiplication systems have encountered practical barriers, particularly because they cannot be integrated, let alone with effective nonlinear processing units. Using a device set designed for digital communication (waveguides, filters, detectors, etc.), PICs have been realized for analog signal processing. The potential of modern PIC platforms to enable large-scale all-optical systems for unconventional and/or analog computing has not yet been investigated.
There has been an emergence of a new class of optical devices that exploit a dynamical isomorphism between semiconductor photocarriers and neuron biophysics, a behavior called spiking. The difference in physical timescales between bio-chemical and electro-optic phenomena allows these “photonic neurons” to exhibit neuron-like behavior on picosecond (instead of millisecond) timescales. This allows them to receive and generate ultrafast signals, i.e. signals with frequency components greater than 1 GHz. Non-spiking neuron behaviors and models, including continuous analog approximations (e.g. Hopfield neurons) and binary, digital approximations (e.g. perceptrons), may also be represented as functions realizable by other electro-optic devices, which are also potentially ultrafast. Despite the variety of possible implementations, “photonic neurons” share a common need for a networking architecture with which many photonic neurons may be interconnected before they may be applied to solve real problems in computing.
As such, a network of ultrafast reconfigurable processors may open computational domains that demand unprecedented temporal precision, power efficiency, and functional complexity, potentially including applications in wideband radio frequency (RF) processing, adaptive control of multi-antenna systems, high-performance scientific computing, real-time control of fast mechanical systems (e.g. hypersonic aircraft), low-latency analysis of financial market data, and high-efficiency simulations aiding in computational neuroscience. Although the ultrafast dynamics of spiking and integrated photonic neurons show potential in this respect, most analyses of them has so far been limited to one or two devices with minimal regard for a compatible network architecture.
Thus, there is a need for a photonic networking architecture configured to address these and other shortcomings of the current systems.